Brat Africa

BraTS-Africa focuses on improving the accuracy and efficiency of brain tumor segmentation in magnetic resonance imaging (MRI) scans from Sub-Saharan African patients. Research emphasizes adapting and improving existing deep learning models, such as U-Net and its variations, to address challenges posed by lower-quality MRI data and the unique characteristics of brain tumors in this population. These efforts aim to enhance diagnostic capabilities and treatment planning in resource-limited settings, ultimately improving patient outcomes.

Papers

November 14, 2024

Exploring Zero-Shot Anomaly Detection with CLIP in Medical Imaging: Are We There Yet?
Aldo Marzullo, Marta Bianca Maria Ranzini
Medical Imaging Single CLIP CLIP Model Zero Shot Anomaly Medical Anomaly Detection Brat Africa

August 21, 2024

Detection of Under-represented Samples Using Dynamic Batch Training for Brain Tumor Segmentation from MR Images
Subin Sahayam, John Michael Sujay Zakkam, Yoga Sri Varshan, Umarani Jayaraman
Data Detection Brain Tumor Segmentation Magnetic Resonance Image Automatic Batching Brat Africa

October 11, 2023

Synthesizing Missing MRI Sequences from Available Modalities using Generative Adversarial Networks in BraTS Dataset
Ibrahim Ethem Hamamci
Generative Adversarial Network Brain Tumor Segmentation Different Modality Glioblastoma Multiforme Brat Africa

August 14, 2023

Automated Ensemble-Based Segmentation of Adult Brain Tumors: A Novel Approach Using the BraTS AFRICA Challenge Data
Chiranjeewee Prasad Koirala, Sovesh Mohapatra, Advait Gosai, Gottfried Schlaug
Deep Learning Segmentation Based Approach Segmentation Model Novel Approach Brain Tumor Segmentation Ensemble Method Brain Tumor Tumor Cell Brat Africa

May 30, 2023

The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa)
Maruf Adewole, Jeffrey D. Rudie, Anu Gbadamosi, Oluyemisi Toyobo, Confidence Raymond, Dong Zhang, Olubukola Omidiji, Rachel Akinola, Mohammad Abba Suwaid, Adaobi Emegoakor, Nancy Ojo, Kenneth Aguh, Chinasa Kalaiwo, Gabriel Babatunde, Afolabi Ogunleye, Yewande Gbadamosi, Kator Iorpagher, Evan Calabrese, Mariam Aboian, Marius Linguraru, Jake Albrecht, Benedikt Wiestler, Florian Kofler, Anastasia Janas, Dominic LaBella, Anahita Fathi Kzerooni, Hongwei Bran Li, Juan Eugenio Iglesias, Keyvan Farahani, James Eddy, Timothy Bergquist, Verena Chung, Russell Takeshi Shinohara, Walter Wiggins, Zachary Reitman, Chunhao Wang, Xinyang Liu, Zhifan Jiang, Ariana Familiar, Koen Van Leemput, Christina Bukas, Maire Piraud, Gian-Marco Conte, Elaine Johansson, Zeke Meier, Bjoern H Menze, Ujjwal Baid, Spyridon Bakas, Farouk Dako, Abiodun Fatade, Udunna C Anazodo
Challenge Task Brain Tumor Segmentation Brain Tumor Glioma Segmentation Diffuse Glioma Brat Africa

December 19, 2022

Multimodal CNN Networks for Brain Tumor Segmentation in MRI: A BraTS 2022 Challenge Solution
Ramy A. Zeineldin, Mohamed E. Karar, Oliver Burgert, Franziska Mathis-Ullrich
Magnetic Resonance Imaging Brain Tumor Segmentation Ensemble Method Glioma Segmentation BRAT Challenge Core Challenge Brat Africa

October 24, 2022

Brain Tumor Segmentation using Enhanced U-Net Model with Empirical Analysis
MD Abdullah Al Nasim, Abdullah Al Munem, Maksuda Islam, Md Aminul Haque Palash, MD. Mahim Anjum Haque, Faisal Muhammad Shah
Convolutional Neural Network Image Segmentation U Net Brain Tumor Segmentation Empirical Analysis Surgical Video Segmentation Brat Africa

Brat Africa

Papers

Exploring Zero-Shot Anomaly Detection with CLIP in Medical Imaging: Are We There Yet?

Detection of Under-represented Samples Using Dynamic Batch Training for Brain Tumor Segmentation from MR Images

Synthesizing Missing MRI Sequences from Available Modalities using Generative Adversarial Networks in BraTS Dataset

Automated Ensemble-Based Segmentation of Adult Brain Tumors: A Novel Approach Using the BraTS AFRICA Challenge Data

The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa)

Multimodal CNN Networks for Brain Tumor Segmentation in MRI: A BraTS 2022 Challenge Solution

Brain Tumor Segmentation using Enhanced U-Net Model with Empirical Analysis